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Article
Publication date: 3 June 2019

Venkata Narasimha Chary Mushinada and Venkata Subrahmanya Sarma Veluri

The purpose of this paper is to empirically test the relationship between investors’ rationality and behavioural biases like self-attribution, overconfidence.

1666

Abstract

Purpose

The purpose of this paper is to empirically test the relationship between investors’ rationality and behavioural biases like self-attribution, overconfidence.

Design/methodology/approach

The study applies structural equation modelling to understand whether individual investors, besides being rational, are subjected to self-attribution bias and overconfidence bias.

Findings

The study shows the empirical evidence in the support of behavioural biases like self-attribution and overconfidence existing besides investors’ rationality. Moreover, there is a statistically significant positive covariance found between self-attribution and overconfidence, implying that an increase/decrease in self-attribution results in the increase/decrease in overconfidence and vice versa. It is also observed that the personal characteristics of an investor such as gender, age, occupation, annual income and their trading experience have an impact on behavioural biases.

Research limitations/implications

The study focused on rational decision making, self-attribution and overconfidence biases using primary data. Further studies can be encouraged to test the existence of behavioural biases based on both market level and individual account data simultaneously.

Practical implications

Insights from the study suggest that the investors should perform a post-analysis of each investment, so that they become aware of past behavioural mistakes and stop continuing the same. This might help investors to minimise the negative impact of self-attribution and overconfidence on their expected utility.

Originality/value

To the best of the authors’ knowledge, this is the first study to examine the relationship among investors’ rationality, self-attribution and overconfidence in the Indian context using a comprehensive survey.

Details

Review of Behavioral Finance, vol. 11 no. 2
Type: Research Article
ISSN: 1940-5979

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Article
Publication date: 9 July 2018

Venkata Narasimha Chary Mushinada and Venkata Subrahmanya Sarma Veluri

The purpose of the paper is to empirically test the overconfidence hypothesis at Bombay Stock Exchange (BSE).

1718

Abstract

Purpose

The purpose of the paper is to empirically test the overconfidence hypothesis at Bombay Stock Exchange (BSE).

Design/methodology/approach

The study applies bivariate vector autoregression to perform the impulse-response analysis and EGARCH models to understand whether there is self-attribution bias and overconfidence behavior among the investors.

Findings

The study shows the empirical evidence in support of overconfidence hypothesis. The results show that the overconfident investors overreact to private information and underreact to the public information. Based on EGARCH specifications, it is observed that self-attribution bias, conditioned by right forecasts, increases investors’ overconfidence and the trading volume. Finally, the analysis of the relation between return volatility and trading volume shows that the excessive trading of overconfident investors makes a contribution to the observed excessive volatility.

Research limitations/implications

The study focused on self-attribution and overconfidence biases using monthly data. Further studies can be encouraged to test the proposed hypotheses on daily data and also other behavioral biases.

Practical implications

Insights from the study suggest that the investors should perform a post-analysis of each investment so that they become aware of past behavioral mistakes and stop continuing the same. This might help investors to minimize the negative impact of self-attribution and overconfidence on their expected utility.

Originality/value

To the best of the authors’ knowledge, this is the first study to examine the investors’ overconfidence behavior at market-level data in BSE, India.

Details

International Journal of Managerial Finance, vol. 14 no. 5
Type: Research Article
ISSN: 1743-9132

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